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Objective To investigate the mechanism of Astragalus membranaceus (AM) in the treatment of vascular dementia (VD) by network pharmacology and molecular docking. Methods The active components of AM were collected from TCMSP database, and the targets of active components were predicted in TargetNet database according to the SMILES. The VD targets were collected by GeneCards database, and the common targets of active components and VD was calculated to obtain the potential targets of AM in the treatment of VD. The active components-target network was constructed by Cytoscape 3.9.1 software. The potential targets of AM in the treatment of VD were imported into STRING database to construct protein-protein interaction (PPI) network, which was analyzed to obtain core targets. The core targets were imported into DAVID database to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The molecular docking was performed to assess the affinity of main active components of AM and the corresponding VD core targets via AutoDock software. Results A total of 20 active components of AM were collected, including jaranol, isorhamnetin, isoflavanone, kaempferol and quercetin, and a total of 102 predicted targets were obtained. A total of 3 556 VD targets were screened, 71 common targets of AM and VD were calculated, and 36 core targets were obtained by PPI analysis, including SLC6A4, ESR1, PTGS2, ABCB1 and AR. A total of 187 GO items and 32 KEGG pathways were enriched, mainly focusing on neurological function, hormone signal and angiogenesis. Molecular docking showed good affinity between the main active components of AM and VD core targets. Conclusion AM treats VD mainly by regulating neurological function, hormone signal and angiogenesis.

Objective To observe the effects of ginsenoside Rg3 (Rg3) in improving fatigue resistance and functionality of skeletal muscle mitochondria in rats at a simulated high altitude. Methods Forty adult male SD rats were randomly divided into 4 groups (n=10), namely the normal group (NG), Rg3-treated normal group (NG+Rg3), model group (MG), and Rg3-treated model group (MG+Rg3). In the latter 2 groups, the rats were exposed to a stimulated altitude of 5 000 m in a hypobaric chamber, and on a daily basis, the rats were taken from the chamber for intragastric administration of 20 mg/kg Rg3 (completed in 1 h). After 15 d of treatment, forced swimming test was performed and 30 min later blood samples were collected from the abdominal aorta for testing the levels of total cholesterol (TC), plasma triglyceride (TG), lactate dehydrogenase (LDH), blood glucose (GLU), blood ammonia (BA) and blood urea nitrogen (BUN); The quadriceps were quickly isolated for detecting malondialdehyde (MDA), Mn-superoxide dismutase (Mn-SOD) and the activity of compound Ⅲ and Ⅳ in the respiratory chain. Results Rg3 treatment significantly increased the swimming time (P < 0.05 or 0.01) and serum levels of TC, TG, LDH and GLU (P < 0.05 or 0.01) and enhanced Mn-SOD activity and mitochondrial respiratory chain complex Ⅲ and Ⅳ activities (P < 0.01) both in rats kept in normal conditions and in those exposed to the simulated high altitude. Rg3 also significantly decreased serum BUN level and MDA content in the skeletal muscle mitochondria in rats exposed to the simulated high altitude (P < 0.01). Conclusion Rg3 can extend forced swimming time, improve the biochemical indexes related to fatigue, and enhance free radical clearance and energy supply of skeletal muscle mitochondria of rats.

Objective: To integrate pharmacovigilance and network toxicology methods to explore the potential adverse drug events (ADEs) and toxic mechanisms of selumetinib, and to provide a reference for quickly understanding the safety and toxicological mechanisms of newly marketed drugs., Methods: Taking selumetinib as an example, this study integrated pharmacovigilance methods based on real-world data and network toxicology methods to analyze its ADE and its potential toxicological mechanism. First, the ADE reports of selumetinib were extracted from the US Food and Drug Administration (FDA) adverse event reporting system (FAERS), and the ADE signals were detected by reporting odds ratio (ROR) and UK medicines and healthcare products regulatory agency (MHRA) methods. The ADE signals were classified and described according to the preferred terms (PTs) and system organ class (SOC) derived from the Medical Dictionary for Regulatory Activities (MedDRA). The network toxicology method was used to analyze the toxicological mechanism of the interested SOCs. The specific steps included predicting the potential targets of selumetinib using TOXRIC, STITCH, ChEMBL, CTD, SwissTargetPreditcion, and Super-PRED databases, collecting the targets of SOC using GeneCards database, conducting protein-protein interaction (PPI) analysis through STRING database, conducting gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis through DAVID database, and testing the molecular affinity using AutoDock software., Results: A total of 1388 ADE reports related to selumetinib were extracted, and 53 positive signals were detected by ROR and MHRA methods, of which 20 signals were not mentioned in the package insert, including ingrowing nail, hyperphosphatemia, cardiac valve disease, hematuria, neutropenia, etc. Analysis of the toxicological mechanism of six SOCs involved in positive ADE signals revealed that the key targets included EGFR, STAT3, AKT1, IL6, BCL2, etc., and the key pathways included PI3K/Akt pathway, apoptosis, ErbB signaling pathway, and EGFR tyrosine kinase inhibitor resistance, etc. Molecular docking assays showed spontaneous binding of selumetinib to key targets in these pathways., Conclusion: The pharmacovigilance analysis identified some new potential ADEs of selumetinib, and the network toxicology analysis showed that the toxic effects of selumetinib may be related to PI3K/Akt pathway, apoptosis, ErbB signaling pathway, EGFR tyrosine kinase inhibitor resistance and other pathways., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Xiong, Lei, Wang, Zhang, Liu, Wang, Liu and Lai.)